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QoS II - Adaptive Virtual Queue - Fair Queueing for Multiple Link. 12 th Mar., 2002 Eun-Chan Park CSL, SoEECS, SNU. S. Kunniyur, R.Srikant “ Analysis and Design of an Adaptive Virtual Queue (AVQ) Algorithm for Active Queue Management ,” SIGCOMM 2001. Contents. Background
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QoS II- Adaptive Virtual Queue - Fair Queueing for Multiple Link 12th Mar., 2002 Eun-Chan Park CSL, SoEECS, SNU
S. Kunniyur, R.Srikant “Analysis and Design of an Adaptive Virtual Queue (AVQ) Algorithm for Active Queue Management,” SIGCOMM 2001
Contents • Background • Congestion control • Active Queue Management • Related works • RED, PI, REM • Adaptive Virtual Queue (AVQ) • AVQ algorithm • Stability analysis • Simulation results • Conclusion
Congestion Control • Congestion control schemes • End-to-end control - TCP-Tahoe, TCP-Reno, TCP-Vegas • Router supported control - AQM: RED, REM, PI control, AVQ
TCP congestion control algorithm • Window-based transmission control sender limits its transmission rate by controlling window size • slow-start, congestion avoidance, fast-recovery • Feedback • Implicit: Timeout, Duplicate ACKs • Explicit Congestion Notification (ECN)
Active Queue Management • Drop-tail queue has several problems • Reduce rates only after overflow loss • Results in significant packet loss • Packet drop could result in a global sync. • Active Queue Management • Resolves the problem of drop-tail • Drops or marks packets at the buffer of router
Random Early Detection (RED) • S. Floyd and V. Jacobson, “random early detection gateways for congestion avoidance,” IEEE/ACM trans. On networking, vol. 1, pp. 397-413, 1993. • Detect congestion using average queue size • Intelligently drop/mark packet before buffer overflow
RED (cont.) • Advantages • Prevent global synchronization • Reduce packet loss • Minimize biases against bursty traffic • Simple, low-overhead • Disadvantages • Difficulty of appropriate parameter setting • Sensitive queueing delay and throughput to the traffic load and to parameters • Argument in the case of small buffer size
Random Exponential Marking (REM) • S. Athuraliya et al., “REM: Active Queue Management,” IEEE Network Magazine May/June. 2001 • “Match Rate, Clear Buffer” • Match aggregated input rate to network capacity • Stabilize queue around a small target • Sum prices • Prices: Differentiated from the calculation of dropping or marking prob. • End-to-End marking prob. exponentially increases with the sum of prices
REM (Cont.) • Link price • Updated periodically • Depends on mismatches of rate and queue length • Marking Prob.
Proportional-Integral (PI) Controller • C.Hollot et al., “On designing improved controllers for AQM routers supporting TCP flows,” IEEE INFOCOM, 2001 • Uses instantaneous queue length, while RED uses EWMA. • Proportional to queue length mismatch and to its accumulation (time integral) • Equivalent to the price of REM
AVQ Algorithm • C : link capacity, : virtual capacity • VQ : virtual queue VQ=B (buffer size) • On a packet arrival, it enqueues VQ, if no rooms available in VQ, marks it • updates on each packet arrival • If input rate is below than desired rate, VC increases and less aggressive marking • Otherwise, VC decreases and more aggressive marking
AVQ Algorithm (cont.) • At a packet arrival • Update VQ size: • If VQ+b > B, then mark packet • Else, VQVQ+b • Update VC
Properties of AVQ • Rate-based marking • Provides early feedback • Achieves input rate to the desired utilization • Regulates utilization instead of queue length as RED,PI,REM • Robust to short flows • Two design parameters (alpha, gamma) determine robustness and stability
TCP/AVQ model for analysis • Similar to stochastic fluid-based TCP dynamics [14] • Ignores slow-start and time-out of TCP • Characterize AIMD • Linearize TCP/AQM model
Stability Analysis of AVQ (1/3) • Main ideas • Take Laplace Transform to the linearized TCP/AVQ model • Obtain the characteristic equation • Find the condition where all roots of char. Eq. is on the LPF.
Stability Analysis (2/3) • Characteristic Eq.
Stability Analysis (3/3) • What value of K yields? • Can it guarantee the unique d? • Make the condition less strict • Find necessary condition
Simulation (1/3) • Compare performance (loss, utilization, avg. queue length) of various AQM schemes when traffic load varies
Simulation (2/3) • Compare responsiveness of AQM schemes when flows are dropped and then established again t= 0 s, N=140 t=100 s, N=35 t=150 s, N=140
Simulation (3/3) • Investigate the effect of short-flow
Conclusion • AVQ algorithm is proposed • Maintains small queue length with consistent utilization and small loss • Robust to short-flows • Stability is analyzed relating to control parameters and feedback delay • A design guideline is provided • However, • Simulation result showing the validity of analysis is missed • Simulation results are unfair (number of packet drop) • Queueing delay is not effectively regulated
J. M. Blanquer, B. Ozden “Fair Queueing for Aggregated Multiple Links,” SIGCOMM 2001
Contents • Introduction & Background • GPS, PGPS (WFQ) • MSFQ • Preliminary properties of MSFQ • Bound on packet delay of MSFQ • Bound on per-flow service of MSFQ • Fairness and MSF2Q • Applications • Conclusion
Introduction • Fair queueing/scheduling is required due to • Increased variety of traffic • diverse requirement for QoS • limited network resources • Fair queueing disciplines based on GPS have been studied considerably in case of single server, however, not in case of multiple server system
Generalized Processor Sharing (GPS) • L. Kleinrock “Queueing Systems Vol 2: Computer Applications,” Wiley, 1976 • GPS server serving N flows is characterized by where, is the amount of traffic for flow i served in • With Leaky Bucket algorithm, it guarantees bandwidth share • Also provides an end-to-end bounded delay service
GPS (Cont.) • Idealized discipline that it can not be implemented • A server can transmit only one packet at a time, not several packets simultaneously • Traffic can not be divided infinitely • As a solution to implementation, several realizable schemes proposed • Packet-by-packet GPS (PGPS), Weighted Fair Queueing (WFQ) • Virtual clock, Self-clocked fair queueing, Start-time fair queueing
Packet-by-packet GPS (PGPS) • K. Parekh, “A Generalized Processor Sharing Approach to Flow Control in IntServ Network,” IEEE Tran. On Networking, 1993 • Also known as Weighted Fair Queueing (WFQ) • A. Demers, et al. “Design and Analysis of a Fair Queueing Algorithm,” SIGCOMM 1989 • Provides guarantees on throughput and worst-case packet delay • Packet delay compared to that of GPS is not grater than the transmission time of one maximum size packet • Bits served for each flow do not fall behind corresponding GPS by more than one maximum size packet
GPS & PGPS • Packet Arrivals of flow 1 and flow 2 < Comparison of GPS & PGPS >
MSFQ Multi-server version of WFQ multi-server version of GPS (MSFQ,N,r) (GPS,1,Nr) • Compare how well (MSFQ,N,r) approximates (GPS,1,Nr) in terms of • worst-case packet delay • amount of traffic served for each flow
Preliminary properties of MSFQ: Total service • Let the total # of bits serviced in by GPS, MSFQ be and , respectively, then • Left ineq. implies: When GPS is busy, MSFQ is busy, too. However, the converse is not true. • Right ineq. implies the need for a buffer size of
Preliminary properties of MSFQ:Waiting time of packet • Upper bound of waiting time for packet k to be scheduled • Pf: Consider the worst case: i) The previous packets have occupied all N server just before the arrival of packet k, ii) all servers finish at the same time
Bound on packet delay of MSFQ (1) • Consider two extreme cases • For GPS, best case: (2) with assumption • For MSFQ, worst case: (3) • (3)-(2) yields (1) • Compare it with the delay in single server
Bound on per-flow service of MSFQ • Maximum difference occurs when • flow i becomes idle in GPS • a packet of flow i begins transmission in MSFQ • Proof done case by case (follow yourself ^^) • For total service: • For a single server:
Fairness of MSFQ • The eq. is incomplete to guarantee fairness • Why? • The eq. does not ensure that the amount of per-flow service does not exceed arbitrary the amount under GPS • i.e., there is no lower limit in the eq. • To resolve this problem • Introduce MSF2 Q, which is an extended version of WF2 Q for multi-server system
MSF2 Q (1/3) • Queued packets at t=0: • ten packets of flow 1 • one packet of each flow 2~N GPS SchedulingMSF2 Q Scheduling
MSF2 Q (2/3) • Scheduling discipline • Define # of outstanding packet of flow i at time t where, outstanding packet is a packet being transmitted of picked for transmission • At time t, when a server is idle and there is a packet to serve, MSF2Q schedules among flows satisfying:
MSF2 Q (3/3) • Properties of MSF2 Q • MSF2 Q provides the lower bound of difference of per-flow service • Similar to WF2Q • Note that MSF2 Q is not work-conserving • Future work: investigate implement of work-conserving scheduler
Applications • Ethernet link aggregation • Cost-effective and fault tolerant solution for scaling the network capacity • IEEE 802.3ad: Standard for Ethernet link aggregation • Access of storage I/O • RAID system with multiple SCIS channels to improve I/O performance • MSF2Q is expected to provide QoS guarantee and fair sharing of multiple I/O channels
Conclusion • Service guarantee and Fairness and for aggregated links have been studied • Extended version of PGPS for multiple server has been analyzed in terms of packet delay and per-flow service • Proposed a new fair queueing in multiple servers, MSF2Q • Future works • Implementation issues • Quantitative comparison to the approach of partitioning flows • Extension of hierarchal GPS and servers with different rates